The modern communications era has brought about a tremendous expansion of wireline and wireless networks. Computer networks, television networks, and telephony networks are experiencing an unprecedented technological expansion, fueled by consumer demand. Wireless and mobile networking technologies have addressed related consumer demands, while providing more flexibility and immediacy of information transfer.
Current and future networking technologies continue to facilitate ease of information transfer and convenience to users by expanding the capabilities of mobile electronic devices. One area in which there is a demand to increase ease of information transfer relates to the delivery of services to a user of a mobile terminal. The services may be in the form of a particular media or communication application desired by the user, such as a music player, a game player, an electronic book, short messages, email, content sharing, web browsing, etc. The services may also be in the form of interactive applications in which the user may respond to a network device in order to perform a task or achieve a goal. Alternatively, the network device may respond to commands or requests made by the user (e.g., content searching, mapping or routing services, etc.). The services may be provided from a network server or other network device, or even from the mobile terminal such as, for example, a mobile telephone, a mobile navigation system, a mobile computer, a mobile television, a mobile gaming system, etc.
The ability to provide various services to users of mobile terminals can often be enhanced by tailoring services to particular situations or locations of the mobile terminals. Accordingly, various sensors have been incorporated into mobile terminals. Each sensor typically gathers information relating to a particular aspect of the context of a mobile terminal such as location, speed, orientation, and/or the like. The information from a plurality of sensors can then be used to determine device context, which may impact the services provided to the user.
Context is any information that can be used to predict the situation of an entity. The entity might be both the user and the device in an environment. Context awareness relates to a device's ability to be aware of its environment, user action and its own state and adapt its behaviour based on the situation.
The accuracy of context extraction algorithms that try to recognize the user's current environment or activity is not close to 100%. One source of problems relates to the training of the statistical environment or activity models in an external computing environment and later the models are used inside a device.
Although models are often trained on a large set of databases collected from multiple users, the results, when the model is used inside a device has just a mediocre accuracy on average for the users, but there might be large differences in accuracy between users. In addition, for example, if the training database for audio-based environment models does not have any data collected in a certain region (e.g. a geological or a political region), the models will not perform well in that region. For example, the street environments sound different in India compared to street environments in Finland. Such systems might benefit from being able to tune or adapt the models to better fit a specific user and his/her life style.